26 Dynamic Tomography of “Pore-Layering” Near Event Horizons

Home ／ Appendix-Prediction and Falsification

This chapter follows the publication template for the falsification program. It uses plain language, avoids equations, and preserves the fixed structure. For general readers: we aim to reconstruct a time-evolving pore-layering pattern—layered on/off openings in radius–time space—within the ring-like light domain and inner quasi-spherical-orbit scales near the event horizon. After removing geometric/calibration terms, scattering/Faraday/plasma effects, and imaging-pipeline biases, we test whether the pattern is (i) cross-frequency consistent (non-dispersive), (ii) shows zero-lag co-occurrence among Stokes I, polarization p, EVPA, and ring-brightness modes, and (iii) exhibits mass–timescale scaling so that curves overlap after normalization by GM/c³. If scattering, Faraday rotation, array-geometry insufficiency, or reconstruction artifacts explain the signals—or robustness is lacking—the claim is disfavored.

I. One-Sentence Goal

Using co-located, co-window dynamic imaging and visibilities, recover a horizon-proximate pore-layering tomogram that satisfies non-dispersion, zero-lag co-occurrence, and GM/c³ scaling across sources. The test focuses on whether a frequency-independent common term drives layered openings rather than medium or pipeline effects.

II. What to Measure

• Layer count and porosity (text grades):
  Within co-located pixels (near ring and throat) and co-window time grains, grade layer count (1/2/3+), inter-layer spacing, and porosity (duty cycle) as strong / medium / weak, with uplift / depression evolution tags.
• Cross-frequency non-dispersion:
  After beam unification + core-shift/scattering deconvolution, compare layer count/phase/strength ranking between 230/345 GHz (optionally 86 GHz). Any λ² / 1/ν flips or scalings imply medium origins.
• Zero-lag co-occurrence:
  For I, p, EVPA, ring-brightness modes m = 1/2, and closure phase, grade zero-lag peaks and side-lobe contrast (strong/medium/weak). Penalize lags exceeding pre-registered thresholds.
• Mass–timescale scaling:
  Normalize time by GM/c³ and compare layer count/phase between M87*, Sgr A*, and other candidates. Reward overlap in phase order across sources rather than frequency-driven drifts.
• Environment linkage:
  Classify enhancement/plateau/neutral trends versus accretion state (magnetically arrested flow vs standard), viewing angle (near-axis vs off-axis), external Faraday depth, and jet-base activity. Expect stronger magnetic flux / near-axis → clearer layering.

III. How to Do It

1. Samples and arrays:
   • Targets: M87* and Sgr A*, plus smaller/larger-mass candidates to stress scaling.
   • Arrays and bands: Event Horizon Telescope (EHT) / Global Millimeter VLBI Array (GMVA) / Very Long Baseline Array (VLBA) / Atacama Large Millimeter/submillimeter Array (ALMA) at 230/345 GHz (optionally 86 GHz) with polarimetric dynamic imaging and closure quantities.
   • Co-windowing: enforce strict concurrency or rapid band rotation, with co-window grades (short/medium/long).
2. Imaging and de-systematics:
   • Beam unification + scattering deconvolution: for Sgr A*, apply stochastic-kernel deblurring and closure-first reconstructions; unify all bands to a common PSF.
   • Core-shift/phase registration: anchor multi-band images/visibilities with optically thin features and ring centers.
   • Polarization calibration: absolute EVPA, D-term leakage, and cross-hand phase with playback on calibrators.
3. Dynamic tomography:
   • Radius–time stacking: in near-ring→throat sectors, build text-graded tomograms for I, p, EVPA, and closure amplitude/phase (layers/phases/porosity).
   • Mode decomposition: extract m = 1/2 ring modes and sub-ring (multi-orbit) tracks, tagging co-occurrence / mis-registration with layers.
   • Zero-lag evaluation: compute zero-lag vs side-lobe grades for I ↔ p/EVPA/modes/closure.
4. Forward prediction, blinding, arbitration:
   • Environment team (forward): using only mass, viewing angle, magnetic-flux state, Faraday-depth proxies, issue prediction cards for layer count/spacing, non-dispersion, and GM/c³ scaling.
   • Measurement teams (independent pipelines): produce closure-first and image-domain regularized reconstructions and layer/lag summaries.
   • Arbitration: align predictions and results; report hit / wrong / null by band/source/pipeline.
5. Controls and artifact stripping:
   • Scattering/Faraday shuffles: repeat with de-scatter vs raw and de-RM vs raw; layering that appears only without corrections is medium-driven.
   • Array-geometry controls: rebuild with sub-arrays and withheld baselines; geometry-sensitive layers are downgraded.
   • Pixel-expansion controls: expand sectors outward to jet base / outer disk; fading layers support a horizon-proximate origin.

IV. Positive/Negative Controls and Removal of Artifacts

1. Positive controls (supporting horizon-proximate layering):
   • 230/345 GHz agree on layer count/phase ranking after beam unification and de-scattering; I, p, EVPA, modes, closure phase show significant zero-lag co-occurrence.
   • After GM/c³ normalization, M87* and Sgr A* overlap in phase order/layer count (amplitude may differ).
   • Magnetically stronger / near-axis cases show clearer layers and more stable spacing.
   • Independent pipelines/sub-arrays/withheld-baseline tests agree; prediction-card hits exceed chance.
2. Negative controls (against horizon layering):
   • Layers flip/scale with λ² / 1/ν, or vanish after de-RM/de-scattering → medium effects.
   • Significance exists only in one pipeline/geometry or is highly regularization-dependent → reconstruction artifacts.
   • GM/c³ scaling fails across sources; signals track large-scale jet events or weather/station noise instead.

V. Systematics and Safeguards (Three Items)

• Interstellar scattering and phase instability (Sgr A*): may fake layers. Safeguard: closure-first + stochastic deblurring, multi-night joint modeling, and report pre/post de-scatter agreement.
• Polarization calibration and Faraday residuals: can mislead EVPA/p layering. Safeguard: multi-band de-RM with sub-band checks; compare de-RM vs raw for direction agreement.
• Sampling and reconstruction bias: sparse u–v coverage yields periodic artifacts. Safeguard: sub-array/withheld-baseline rebuilds, synthetic injection tests, and pipeline swaps; down-weight geometry-sensitive layers.

VI. Execution and Transparency

Pre-register targets/bands, co-window tolerances, beam/de-scatter/de-RM workflows, text-grade rules for layer count/porosity/spacing, zero-lag and GM/c³ scaling criteria, controls/exclusions, and arbitration. Maintain hold-out nights/windows and withheld baselines per source–band. Enable cross-team/pipeline replication by exchanging visibilities/closure data and scripts; run down-sampling/noise/scatter-kernel variants. Release prediction cards, layering grade tables, zero-lag and scaling summaries, scatter/polarization/array logs, and key intermediates. This chapter links with Chapters 7 (co-located scaling near black-hole rings), 22 (jet-base brightness–polarization coupling), 12 (engineered-vacuum in cavity QED), and 25 (steady-state Schwinger crossing) for a horizon–vacuum layering cross-check.

VII. Pass/Fail Criteria

1. Support (passes):
   • Multi-band, multi-pipeline, multi-array detection of non-dispersive, zero-lag multi-layer tomography.
   • GM/c³ normalization yields phase-order/layer-count overlap across sources; layering strengthens in magnetically rich / near-axis subsets.
   • Prediction-card hit rates exceed chance and remain after de-scatter/de-RM and geometry hold-outs.
2. Refutation (fails):
   • Layering follows dispersive laws or disappears after medium corrections.
   • Significance is pipeline/geometry specific or regularization sensitive.
   • Cross-source scaling fails; environment trends are non-monotonic; arbitration hits are near chance.